Data Analyst with Security Clearance

Senior Data Analyst Location: Washington, DC | Hybrid, 4 Days per Week Onsite Experience: 7+ Years Required Clearance: Secret clearance preferred; ability to obtain required Public Trust/background suitability Position Overview We are seeking a hands-on Senior Data Analyst to architect analytical solutions, build data models, develop dashboards, and transform complex datasets into meaningful business insights. This position requires advanced SQL, Python, and Power BI experience along with the ability to independently develop analytical solutions from initial requirements through final delivery.

The successful candidate will also provide technical guidance to junior analysts and may lead smaller analytical workstreams. Experience working with financial data is highly valuable, as is familiarity with AWS and Azure cloud environments.

Key Responsibilities
Lead advanced analytical projects involving large and complex datasets. Design analytical solutions that transform business requirements into scalable data and reporting products. Identify trends, performance drivers, risks, anomalies, and actionable insights from enterprise data. Extract and combine information from multiple systems to create reliable analytical datasets. Develop and optimize complex SQL queries, views, scripts, and data transformation logic. Use Python for data extraction, cleansing, transformation, validation, statistical analysis, and automation.

Design reusable datasets and data models supporting dashboards and recurring reporting. Build and enhance interactive Power BI dashboards and business intelligence products. Develop advanced DAX and Power Query/M solutions. Use Python alongside Power BI when advanced statistical analysis or custom visualization capabilities are required. Apply statistical modeling techniques to forecasting and analytical problems. Build ad hoc and recurring reports for leadership and operational users. Define and document KPIs, metrics, business rules, and reporting requirements.

Perform data profiling, reconciliation, validation, and quality assurance. Automate repeatable data and reporting processes. Translate sophisticated technical findings into understandable recommendations for non-technical audiences. Support dashboard testing, user acceptance testing, defect resolution, and stakeholder feedback. Lead smaller technical workstreams and coordinate assignments, priorities, risks, and deliverables. Mentor junior analysts and review technical work products.

Maintain documentation including data dictionaries, lineage information, analytical assumptions, and user guidance. Required Qualifications
7+ years of professional experience across data analytics, business intelligence, data science, reporting, data engineering, or related disciplines. Strong hands-on SQL experience, including developing and optimizing complex queries.

Strong Python experience for data analysis, transformation, and automation.
3+ years of experience working with Python libraries and frameworks such as: pandas
NumPy
Matplotlib
DataFrame-based data processing
Strong Power BI dashboard development experience.
3+ years of experience developing complex DAX and Power Query/M logic involving financial data. Experience developing dashboards and visualizations using Power BI and Tableau. Hands-on ETL experience involving data extraction, cleansing, transformation, validation, and integration.

Experience developing reusable datasets and data models for analytics and reporting. Experience with statistical modeling and forecasting techniques such as:
Linear regression
Logistic regression
Time-series forecasting
Experience automating analytical or reporting workflows.
5+ years of finance or accounting experience. Experience developing ad hoc and recurring decision-support reporting. Experience leading smaller technical teams or analytical workstreams. Strong communication skills with the ability to explain technical findings to non-technical audiences.

Strong analytical, problem-solving, and data-quality skills. Bachelor's degree in Data Analytics, Data Science, Information Systems, Computer Science, Statistics, Mathematics, Finance, Business, or a related discipline.

Preferred Qualifications
Experience designing or architecting end-to-end analytics solutions.
AWS experience.
Microsoft Azure experience.
Experience working with financial, budgeting, accounting, or forecasting data.
Experience using Python within Power BI.
Experience developing enterprise KPI and executive reporting solutions.
Experience supporting cloud-based data and analytics platforms.
Experience within regulated or public-sector environments.
Interview Process
Single primary interview.
Candidates should expect a practical SQL coding assessment as part of the evaluation process.